Continuity, traditionally, encompasses best practices and processes that can be applied only to the resources they are designed to protect. For example when two database servers are run across geographies and a database log shipping strategy is used to keep them continuous. Another example is when hypervisor based replication is used to keep two geographically separated virtual machines continuous.
The above mentioned examples imply 1:1 relationships between the two sides of a continuity strategy (endpoints) and constrain the service provider because intimate knowledge of resource/process requirements of the strategy is required to make it work.
To this end, cloud infrastructures are used in Information Technology Enterprises to achieve continuity in various forms such as data replication, availability zones, orchestration, virtual machine motion, distributed state queues etc. However, continuity achieved by the available cloud infrastructures is limited in that high levels of continuity are not available across entities such as entire data centers, entire clouds, applications/services that span datacenters/clouds, virtual companies, virtual offices, network segments, etc. that scale massively with respect to resources like servers, networks, storage, etc. that are contained within them. There are several disadvantages associated with the available clouds infrastructure, thereby limiting its continuity, such as:                Each resource of the cloud infrastructure such as, being not limited to Servers (virtual machines, bare metal, software designed, etc.). Storage (disks, storage arrays, file systems etc.), Services (Infrastructure-IaaS, Compute-CaaS, Software-SaaS, Platform-PaaS, IT-ITaaS etc.), applications, virtual and physical networks has a different notion of continuity and it becomes extremely difficult to achieve combined continuity when dissimilar resources are combined. For example, a datacenter has several applications, heterogeneous hardware and processes. Each set of applications have their own notion of continuity based on their criticality and capability. In other words, the criticality of an application serving CRM data might be high but the criticality of an application serving financials might be even higher. The business continuity parameters in terms of time and data are high in the case of former and correspondingly higher for the latter. In the case of 100s of such applications and processes, all tied together under a single continuity expectation combined with the fact that each cloud resource has a certain continuity capability in terms of RPO/RTO and cannot exceed the said capabilities, it becomes almost impossible to offer uniform business continuity for all the resources together.        All the cloud platforms are not uniform in a cloud infrastructure and may offer different notions of continuity. Cloud platforms are essentially software stacks that give different capabilities in terms of continuity like hypervisor replication, replicated object buckets, resource specific orchestration, etc. For example, cloud platforms presently available in the market have different capabilities. Some cloud platforms does not have hypervisor based replication while some have. Some cloud platforms do have a hypervisor based replication which does not perform well. Some clouds do not have the ability to manage non windows based hypervisors completely while some clouds have the above said capability. The problem becomes complex when one has to offer business continuity across all kinds of technologies and platforms.        Available clouds may comprise legacy applications which are not cloud specific or are not intelligently responsive to the behavior of clouds. Legacy applications are prone to data continuity issues.        Inability of clouds to apply the same continuity parameters together to a set of resources like application sets, heterogeneous hardware, datacenters, branch offices etc. and achieve high levels of continuity. This is true even if applications are cloud specific due to interdependencies between application and the business process. For example, a single service level agreement (SLA) is applied which contains RTO/RPO, geographic preferences, operating model preferences like hot, warm, cold, etc. and other requirements to an ERP application that spans multiple datacenters, cloud software, storage arrays and networks. There is no infrastructure to ensure that such an operation can be considered or even carried out. This knowledge also implies that there is no provision today to ensure that the SLA itself can be maintained consistently. This is because business continuity was always managed end to end and depended on uniform hardware/software capabilities across the spectrum.        Dynamism of clouds which means continuous change in clouds with new capabilities, size of deployment, resource uses, infrastructure changes, workload migrations. Any continuity solution chosen must keep changing to adapt to the continuous changes in the clouds.        Lack of interoperability between dissimilar clouds. What may work in one cloud does not work in the other cloud. Standard infrastructures like storage, compute, network, application are converging together into a single hardware offering ensuring that massive scaling of resources is possible for the same datacenter footprint. Public clouds are pushing the technology envelope in a commoditized direction while private/hybrid clouds are clinging to the existing technologies and trying to retrofit the cloud for it.        Tiering of resources is seen as central to cloud management and this increases decision making complexity exponentially with tiers encompassing hypervisors, clouds, providers, services, applications, storage, compute and even networks.        Continuously variable demand from customers where services can be started/paused/continued/revised/resized/stopped fairly quickly which requires high levels of continuity.        Customers have different kinds of applications and expectations in terms of continuity parameters like cost, SLA's and level of protection and the service provider has to cater to them        Maintenance of Service Level Agreements (metrics) across hundreds of protected resource profiles especially when they need to be balanced against catastrophic grid failures, over utilization of resources, multi tenancy and security profiles.        In order to provide continuity today there needs to be a 1:1 relationship between resources that are connected together as part of the continuity process and this requirement means that service providers cannot optimize on continuity cost using multi tenancy capabilities.        